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Yayın Channel modelling and characterization for VLC-based medical body sensor networks(Işık Üniversitesi, 2022-01-10) Dönmez, Barış; Miramirkhani, Farshad; Işık Üniversitesi, Lisansüstü Eğitim Enstitüsü, Elektrik - Elektronik Bölümü Yüksek Lisans ProgramıOptical Wireless Communication (OWC) refers to transmission in unguided propagation media through the use of optical carriers, i.e., visible, Infrared (IR), and Ultraviolet (UV) bands. In this thesis, we focus on indoor Visible Light Communication (VLC)-based Medical Body Sensor Networks (MBSNs) which allow the Light Emitting Diodes (LEDs) to communicate between on-body sensors/subdermal implants and on-body central hubs/monitoring devices while also serving as a luminaire. Since the Quality-of-Service (QoS) of the communication systems depends heavily on realistic channel modeling and characterization, this thesis aims at presenting an up-to-date survey of works on channel modeling activities for MBSNs. After the introduction chapter, the second chapter presents the literature survey and the first section reviews existing IR-based MBSNs channel models based on which VLC channel models are derived. The final section of this chapter provides comprehensive details on existing VLC-based MBSNs channel models. Third chapter presents a realistic channel modeling approach called site-specific ray tracing that considers the skin tissue for the MBSNs channel modeling for realistic hospital scenarios. In addition, channel characteristics which are the channel DC gain and RMS delay spread values that are extracted from the sample Channel Impulse Responses (CIRs) among extensive amount of static channel modelling simulations are demonstrated. Fourth chapter proposes a random trajectory generator and implements it in mobile channel modelling and characterization for the two of the aforementioned real-life based scenarios. Then, the CIRs and channel characteristics are obtained then by utilizing the simulation results data, the spatial distribution of channel characteristics and curve fitting on histograms of these are illustrated with explanations.
